Machine learning for identification of short-term all-cause and cardiovascular deaths among patients undergoing peritoneal dialysis.
Xu X, Xu Z, Ma T, Li S, Pei H, Zhao J, Zhang Y, Xiong Z, Liao Y, Li Y, Lin Q, Hu W, Li Y, Zheng Z, Duan L, Fu G, Guo S, Zhang B, Yu R, Sun F, Ma X, Hao L, Liu G, Zhao Z, Xiao J, Shen Y, Zhang Y, Du X, Ji T, Wang C, Deng L, Yue Y, Chen S, Ma Z, Li Y, Zuo L, Zhao H, Zhang X, Wang X, Liu Y, Gao X, Chen X, Li H, Du S, Zhao C, Xu Z, Zhang L, Chen H, Li L, Wang L, Yan Y, Ma Y, Wei Y, Zhou J, Li Y, Dong J, Niu K, He Z; PDTAP Working Group.
Xu X, et al. Among authors: li l.
Clin Kidney J. 2024 Aug 29;17(9):sfae242. doi: 10.1093/ckj/sfae242. eCollection 2024 Sep.
Clin Kidney J. 2024.
PMID: 40040752
Free PMC article.
We aimed to develop and validate machine learning-based models to predict near-term all-cause and cardiovascular death. Machine learning models were developed among 7539 PD patients, which were randomly divided into a training set and an internal test set by five random sh …
We aimed to develop and validate machine learning-based models to predict near-term all-cause and cardiovascular death. Machine learn …